Content
Introduction
This Applied Use Guide outlines best practices for using AI in customer support, ranging from chatbots to sentiment analysis, to ensure an efficient, fair, and empathetic service experience.
Reason Why
AI can make customer support faster and more scalable, providing instant help and triaging complex queries. Yet biases in chatbots, data privacy concerns, or the absence of human empathy can lead to impersonal or even harmful interactions. Balancing automation with the human touch is key to delivering truly helpful and ethical service.
Key Principles
- Transparency: Let customers know when an AI chatbot is responding vs. a human agent, so they can gauge the nature of the interaction.
- Fairness: Ensure that AI-driven support systems treat all customers equally, regardless of language, disability status, or geographic origin.
- Privacy: Adhere to data regulations when using customer info to train support models, and store user data securely.
- Empathy: Aim for sensitivity in language and tone; design chatbots or AI assistants to handle emotional customers with care.
- Escalation Path: Provide an easy option for customers to switch to human agents when issues are complex or personal.
Best Practices
- Clear Communication: Disclose when customers are chatting with AI, and set expectations about what the AI can and cannot handle.
- Ensure Data Security: Encrypt customer data, limit data retention, and mask sensitive info in logs or training sets.
- Monitor and Mitigate Bias: Periodically review chatbot transcripts to identify potential biases—e.g., responding differently based on user accent or perceived demographics.
- Maintain Human Oversight: Agents should periodically review complex or unusual queries. AI can assist but may fail in nuanced scenarios.
- Support Inclusive Design: Accommodate customers with disabilities (e.g., voice-based interfaces for the visually impaired) and ensure your AI system handles diverse dialects or non-native speakers gracefully.
Specific Techniques
Technique 1: Automated Responses
Default Prompt: Generate automated responses for common customer inquiries.
Updated Prompt: Generate automated responses for common customer inquiries. Clearly indicate that they’re AI-generated, use respectful and neutral language, and ensure that sensitive data (like account numbers) is never included in the text.
Technique 2: Sentiment Analysis
Default Prompt: Analyze customer feedback to identify sentiment trends.
Updated Prompt: Analyze customer feedback to identify sentiment trends, ensuring privacy compliance. Explain your data sources and how you mitigate bias in sentiment detection, particularly for slang or multilingual inputs. Provide action steps for negative feedback.
Technique 3: Chatbot Interaction
Default Prompt: Develop a chatbot script for troubleshooting technical issues.
Updated Prompt: Develop a chatbot script for troubleshooting technical issues. Clearly communicate that the chatbot is AI-driven, use inclusive language, and offer a quick way to escalate to a human rep. Address potential pitfalls for advanced or unique user setups.
Technique 4: Personalized Support
Default Prompt: Offer personalized support recommendations based on customer data.
Updated Prompt: Offer personalized support recommendations based on customer data, explicitly stating how personal info is used and stored. Ensure these recommendations are fair and free from discriminatory assumptions, and clarify how customers can opt out of data-based personalization.
